Xiao-Li Meng is affiliated with Harvard University in the United States and primarily works within the field of Mathematics. Their research contributions span several subfields, including Statistics and Probability, Artificial Intelligence, Epidemiology, Management Science and Operations Research, and Modeling and Simulation.
The scientist's work covers a range of topics, most notably Statistical Methods and Bayesian Inference, Statistical Methods and Inference, Advanced Statistical Methods and Models, COVID-19 epidemiological studies, Data-Driven Disease Surveillance, Vaccine Coverage and Hesitancy, and Statistics Education and Methodologies.
Frequent collaborators of Xiao-Li Meng include Ruobin Gong, Valerie C. Bradley, Shiro Kuriwaki, Michael Isakov, and Dino Sejdinović. The breadth of these collaborations indicates a consistent focus on interdisciplinary approaches to statistical research and applied science.
The scientist has published extensively in several venues, notably Harvard Data Science Review, arXiv (Cornell University), Statistical Science, Journal of the American Statistical Association, and The New England Journal of Statistics in Data Science. These publications reflect active engagement with both theoretical and applied statistics communities.
Selected recent publications include:
Steve Brooks;Andrew Gelman;Galin L. Jones;Xiao-Li Meng
Xiao-li Meng;Robert Rosenthal;Donald B. Rubin
Andrew Gelman;Xiao-Li Meng;Hal Stern
Xiao Li Meng;Donald B. Rubin
Andrew Gelman;Xiao Li Meng
David A van Dyk;Xiao-Li Meng
Xiao-Li Meng;Wing Hung Wong
Xiao-Li Meng;David Van Dyk
Xiao-Li Meng
Gregory C. Reinsel;George C. Tiao;Xiao Li Meng
John Barnard;Robert McCulloch;Xiao Li Meng
Xiao-Li Meng;Donald B. Rubin
Xiao-Li Meng
John Barnard;Xiao Li Meng
Xiao-Li Meng;Donald B. Rubin
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K H Li;X L Meng;T E Raghunathan;D B Rubin
Xiao-Li Meng
Yaming Yu;Xiao-Li Meng
X.-L. Meng;D. A. Van Dyk
Andrew Gelman;Xiao-Li Meng
Steve Brooks;Andrew Gelman;Galin Jones;Xiao-Li Meng
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